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Evolving Clustering Algorithms And Their Application For Condition Monitoring, Diagnostics, & Prognostics, Fling Finn Tseng
Evolving Clustering Algorithms And Their Application For Condition Monitoring, Diagnostics, & Prognostics, Fling Finn Tseng
Wayne State University Dissertations
Applications of Condition-Based Maintenance (CBM) technology requires effective yet generic data driven methods capable of carrying out diagnostics and prognostics tasks without detailed domain knowledge and human intervention. Improved system availability, operational safety, and enhanced logistics and supply chain performance could be achieved, with the widespread deployment of CBM, at a lower cost level. This dissertation focuses on the development of a Mutual Information based Recursive Gustafson-Kessel-Like (MIRGKL) clustering algorithm which operates recursively to identify underlying model structure and parameters from stream type data. Inspired by the Evolving Gustafson-Kessel-like Clustering (eGKL) algorithm, we applied the notion of mutual information to …